As is widely recognized, LTE is a standard governing wireless communications between devices such as mobile phones and data terminals on the one hand and base stations/eNodeB elements on the other hand. The standard was developed by the 3GPP (3rd Generation Partnership Project), which periodically issues updates in response to the ever increasing flux in the demands of the telecommunications industry and consumers of its products. The updates are commonly referred to as, “Releases.” Often, the Releases are prompted by a variety of needs including, for example, a desire to increase the efficiency of operations between devices with minimal change to the operation and infrastructure of the network of a service provider. In other words, the costs related to device manufacture, compatibility of the network and services to be provided by the network are often paramount concerns when devising a particular Release.
Circa 2009, the Internet was in a stage of its evolution in which the backbone (routers and servers) was connected to edge nodes formed primarily by personal computers. At that time, Kevin Ashton (among others) looked ahead to the next stage in the Internet's evolution, which he described as the Internet of Things (“IoT”). In his article, “That ‘Internet of Things’ Thing,” RFID Journal, Jul. 22, 2009, he describes the circa-2009-Internet as almost wholly dependent upon human interaction, i.e., he asserts that nearly all of the data then available on the internet was generated by data-capture/data-creation chains of events each of which included human interaction, e.g., typing, pressing a record button, taking a digital picture, or scanning a bar code. In the evolution of the Internet, such dependence upon human interaction as a link in each chain of data-capture and/or data-generation is a bottleneck. To deal with the bottleneck, Ashton suggested adapting internet-connected computers by providing them with data-capture and/or data-generation capability, thereby eliminating human interaction from a substantial portion of the data-capture/data-creation chains of events.
In the context of the IoT, a thing can be a natural or man-made object to which is assigned a unique ID/address and which is configured with the ability to capture and/or create data and transfer that data over a network. Relative to the IoT, a thing can be, e.g., a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low, field operation devices that assist fire-fighters in search and rescue, personal biometric monitors woven into clothing that interact with thermostat systems and lighting systems to control HVAC and illumination conditions in a room continuously and imperceptibly, a refrigerator that is “aware” of its suitably tagged contents that can both plan a variety of menus from the food actually present therein and warn users of stale or spoiled food, etc.
In the post-2009 evolution of the Internet towards the IoT, a segment that has experienced major growth is that of small, inexpensive, networked processing devices, distributed at all scales throughout everyday life. Of those, many are configured for everyday/commonplace purposes. For the IoT, the edge nodes will be comprised substantially of such small devices.
Within the small-device segment, the sub-segment that has the greatest growth potential is embedded, low-power, wireless devices. Networks of such devices are described as comprising the Wireless Embedded Internet (“WET”), which is a subset of IoT. More particularly, the WET includes resource-limited embedded devices, which typically are battery powered, and which are typically connected to the Internet by low-power, low-bandwidth wireless networks (“LoWPANs”).
In 2016, the 3GPP issued its Release 13. This Release addressed revisions to the LTE (4G) standard for LTE-M prescribed communications. Such revisions particularly focused on addressing aspects aimed at enabling the following: reduced cost of LTE devices for a wide variety of IoT applications; improved battery life for such devices when executing such applications; and improved network coverage enabling users to accomplish desired goals.
Generally, Release 13 addresses a low-power, wide-area network (LPWAN) technology for the IoT enabling decreased device complexity in regard to operation with an existing LTE network. More specifically, and in order to accomplish the aforementioned decrease in device complexity, the Release provides for several reductions in comparison to LTE maximums. They include reductions in each of maximum bandwidth, maximum transmission/reception rates, and maximum transmission power. Accordingly, devices operating in accordance with these reductions require less componentry, and are thus less expensive to produce. At the same time, and owing to their less sophisticated design, such devices draw less power and thus conserve battery reserve, while at the same presenting a substantially lesser burden on the network with which they are connected. Further provided by Release 13 is an adaptability for variation of power mode, also enabling a device to experience significant battery conservation.
Across the broad spectrum of IoT applications including, but not limited to, wearables, smart metering, sensor systems, and asset tracking, LTE-M represents a highly beneficial framework in at least the following respects. First, as a device's required complexity decreases, so does its cost. Second, because of such decreased complexity, the incumbent network, likewise, experiences a reduced cost of adaptation. Third, due to decreased power burden on the device, battery life may be extended significantly. Fourth, since data transmission rates are decreased, so are the actual monetary costs of data services provided by the LTE network provider.
An example use case in which LTE-M is highly desirous is a situation in which smart metering provides for the communication of a relatively small amount of data, i.e., a meter reading, at a scheduled time.
Accordingly, it would be desirable to optimize the implementation of LTE-M communication so as to improve the cost-benefit environment associated with conducting such metering and other applications in which LTE-M is pertinent, in accordance with, for example, varied scheduling for the occurrence of communications, varied environmental (i.e., device and/or network) conditions in/under which operations occur, and varied “demand” operation resulting from commands for such operation.